It is often assumed that migrating to cloud computing is purely a technical move, but how can it help companies in terms of improving their business models, support business transformation efforts and deliver value?
Any migration, including moving to the cloud, must be based on business value. Typical reasons organizations adopt the cloud include to take advantage of the ability to scale quickly and drive efficiency while focusing on core priorities.
Crucially, cloud can be an enabler for innovation. In a recent EY survey that looked at how rethinking your cloud strategy can help you reshape your business, 35% of executives stated that cloud-native development will lead to improved innovation and stronger ability to develop new revenue streams. By lowering the barriers to entry for new apps and automation, employees at various levels can contribute ideas that transform the business model through bottom-up innovation.
Rapid technology advancements, including AI and Generative AI, are changing how businesses operate. The ability to use these new technologies is critical to survive and thrive and leveraging the cloud for these technologies is a necessity.
Cloud Leader for EY Global Delivery Services.
Along with AI, the cloud plays a pivotal role in enabling better insights and experience via data and analytics by making it easier to use the latest technologies with elastic scaling.
Additionally, well-architected cloud solutions can provide cost savings when compared to traditional on-premises solutions if designed and implemented optimally. Also, moving to an Opex model can help with cash flow and offer flexibility for organizations. Well-architected solutions designed to use the right combination of services and regions can also help reduce a company’s overall carbon footprint, helping to achieve sustainability goals.
Security and data privacy is an important requirement for all businesses. While the cloud itself does not necessarily provide any guarantees, it is important to understand that hyperscalers have invested billions on best practices, including encryption, key vaults, identity and access management, and threat detection. They also comply with many regulations including GDPR, HIPAA, and PCI-DSS. The onus, however, is still with the organization to implement all best practices to ensure security.
In the past, business continuity, including disaster recovery, involved standing up alternate data centers with high levels of availability. Today, the cloud makes it easier and less expensive to stand-up applications using “as-a-code” approach.
In the world of digital transformation, cloud is the foundation, and it must be seen as not just an infrastructure play, but as a proxy for all technologies.
How does cloud migration factor into AI adoption for companies?
By migrating to the cloud, organizations can take advantage of cutting-edge technologies like artificial intelligence, machine learning, and big data analytics. In the survey, 84% of participants said AI adoption would not have been possible without cloud migration. Cloud offers the ability to reimagine operations, create agile business models, and harness AI.
The adoption of AI services on the cloud, however, requires organizations to adopt the cloud more broadly rather than just rely on it for specific or siloed AI use cases.
For example, a universal approach to data, cloud, and AI can help companies get a better bird’s eye view of operations and customer behavior. Having access to a larger and more diverse dataset allows for more accurate and reliable analysis, making AI outcomes better. This continuous influx of real-time data in the cloud creates an ideal environment for evolving AI models. These models can adjust and learn as new data flows in, forming the foundation of an agile and intelligent business ecosystem.
We believe that cloud has the potential to democratize access to AI by breaking down siloes and technical complexities to help create an accessible and collaborative environment where cross-functional teams can share ideas and innovate collectively.
How is AI transforming cloud migration?
AI is completely transforming end-to-end cloud migration & modernization life cycles. Overall, we see that GenAI-infused tools, including the use of AI agents, help significantly improve productivity across the entire migration/modernization lifecycle. GenAI intervention is increasingly important when it comes to optimally executing large scale migration programs at scale, helping to enhance quality, consistency, and risk mitigation. Examples include the use of AI tools to support cloud migration risk and planning, scenario testing, cybersecurity in cloud operations, and cost.
Many companies believe that their cloud migrations would have been useful, but that they were not implemented effectively
Companies can face barriers or challenges when it comes to cloud migration, especially in highly regulated industry fields such as banking, capital markets, wealth and asset management, insurance, healthcare, public sector, and government. This includes seeing cloud migration as purely an IT project; 50% of IT executives surveyed told EY that their cloud strategy was part of their technology transformation efforts while only 27% said the aim was business transformation.
Lack of executive commitment, organizational buy-in, and stakeholder availability are also challenges. Only 16% of companies we surveyed were looking at using cloud to evaluate new business models.
Other challenges include a lack of governance, a shortage of skills and knowledge, organization readiness, and a lack of planning or budgeting.
How can organizations readjust and recalibrate following a less-than-optimal cloud migration to deliver true value?
To set a migration up for success, we recommend that companies clearly define their cloud strategy and governance framework from the outset, with the process being led by a Cloud Transformation Office that incorporates all relevant stakeholders, who should frequently refresh their business case for cloud migration as necessary and course correct as needed to ensure the value gap is minimized.
Secondly, if a value gap does appear, it is crucial the specific reasons behind it are fully understood. For example, this includes always revisiting and reflecting upon the original business case, addressing cost overruns through FinOps best practices, validating the people strategy, including upskilling and creating new roles, and revisiting the overall IT procurement approach in the cloud world.
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